similar to: All subsets weighted regression in R ?

Hi, I have found a minor problem with leaps(). In 1.3.1 under Windows 2000 I seem to only be able to obtain values for one statistic at a time. That is choosing method=c("Cp","adjr2","r2") just gives Cp values. To mimic the output of Minitab's MTB > BReg 'Fertility' 'Agriculture'-'Infant.Mortality' ; SUBC> NVars 1 5; SUBC>

Hello dear R-help members, I recently became interested in using biglm with leaps, and found myself somewhat confused as to how to use the two together, in different settings. I couldn't find any example codes for the leaps() package (except for in the help file, and the examples there are not as rich as they could be). That is why I turn to you in case you could share some good tips and

Hello I am trying to use all subsets regression on a test dataset consisting of 11 trails and 46 potential predictor variables. I would like to use Mallow's Cp as a selection criterion. The leaps function would provide the required output but does not work with this many variables (see below). The alternative function regsubsets should be used, but I am not able to define the function in

Hello, I have a question about doing ALL possible subsets regression with a general linear model. My goal is to produce cumulative Akaike weights for each of 7 predictor variables-to obtain this I need R to: 1. Show me ALL possible subsets, not just the best possible subsets 2. Give me an AIC value for each model (instead of a BIC value). I have tried to do this in library(RcmdrPlugin.HH),

Hi all I am hoping this is just a minor problem, I am trying to implement a best subsets regression procedure on some ecological datasets using the regsubsets function in the leaps package. The dataset contains 43 predictor variables plus the response (logcount) all in a dataframe called environment. I am implementing it as follows: library(leaps)

Hello, I am working on a variable selection problem and I wonder whether there is some function or package in R works similar to the 'PROC REG' in SAS? Thank you. Some facts about 'PROC REG': PROC REG in SAS first composes a crossproducts matrix. The matrix can be calculated from input data, reformed from an input correlation matrix, or read in from an SSCP data set. For each

Dear R-users, Is anyone successfully using leaps() and particularly subsets() (contributed function) in R? When I attempt to run them with modest matrices, R promptly faults and dumps the core. Also, how does one use subsets.formula() within subsets()? R : Copyright 1997, Robert Gentleman and Ross Ihaka Version 0.50 Alpha-4 (September 10, 1997) R-base-0.50.a4-1.i386.rpm

Hello List, I was wondering if a package or piece of code exists that will allow all possible subsets regression model selection within program R. I have already looked at step(AIC) which does not test differing combinations of variables within a model as far as I can tell. In addition I tried to use the leaps command, but that does not use the criterion I am looking for. Any help or advice

Hi In trying to fit a linear model , I use the leaps() function to determine wich predictors I should include in my model. I would like to plot the Mallow's Cp criteria against p with the indexes of selected model variates as points labels Is there already such a function? (I could not find it) Thanks Anne [[alternative HTML version deleted]]

I have spent a fair amount of time looking for a package that is automated to run glm (binomial) regression models with all possible subsets of my independent variables. Something akin to Lumley's "leaps" package, but can be applied to glms, not just lms; or something similar to Stata's brute force "tryem" function? If anyone can point me in the right direction I

Dear all I am supposed to use Mallow's Cp creterion to select a model which require a "leaps" package. the version right now I am using is R 1.7.1(os:windows), the "leaps" package is not included. please let me know how and where can I get this package and add it to the current version, any caution on adding this package is highly appreciated. thank you best

Hey folks, I'm trying to do all subsets on a zero-inflated poisson regression. I'm aware of the leaps and regsubsets functions but I don't know if they work for ZIP regressions or how the syntax fits in for them. Can anyone help? The model syntax is: > zip.zc <- zicounts(resp=Scars~.,x=~Location + Lar + Mass + Lac + Lar:Mass + Location:Mass, data = alan2,

Dear all, Does R or S-plus or any of their packages provide any command to form any of the following procedures to find Best Regression Equation - 1. 'All Possible Regressions Procedures' (is there any automated command to perform 2^p regressions and ordering according to criteria R2(adj), mallows Cp, s2- by not setting all the regression models manually), 2. 'Backward

Dear R-users, For the purpose of model selection I am looking for a way to exhaustively (and efficiently) search for best subsets of predictor variables for a logistic regression model. I am looking for something like leaps() but that works with glm. Any feedback highly appreciated. -- Harald von Waldow <hvwaldow at chem.ethz.ch> Safety and Environmental Technology Group Institute for

Hi, I am trying to fit all subsets for a vector autoregression with exogenous variables. I have been looking at the 'leaps' function but I not sure how to get it to work when lags for each variable are included in the model. I would be really appreciative if someone could provide some links to examples. Thanks in advance! -- View this message in context:

Dear List members I am using the regsubsets function to select a few predictor variables using Mallow's Cp: > sel.proc.regsub.full <- regsubsets(CO2 ~ v + log(v) + v.max + sd.v + tad + no.stops.km + av.stop.T + a + sd.a + a.max + d + sd.d + d.max + RPA + P + perc.stop.T + perc.a.T + perc.d.T + RPS + RPSS + sd.P.acc + P.dec + da.acc.1 + RMSACC + RDI + RPSI + P.acc + cov.v + cov.a +

R-packages leaps and subselect implement various methods of selecting best or good subsets of predictor variables for linear regression models, but they do not seem to be applicable to logistic regression models. Does anyone know of software for finding good subsets of predictor variables for linear regression models? Thanks. -Ben p.s., The leaps package references "Subset Selection

>?step .... 'step' uses 'add1' and 'drop1' repeatedly; it will work for any method for which they work, and that is determined by having a valid method for 'extractAIC'. When the additive constant can be chosen so that AIC is equal to Mallows' Cp, this is done and the tables are labelled appropriately. so my question is :what constant

Hello R users, I have three questions and I would be grateful if someone could give me an answer to each of these. 1) I have constracted a function that returns an output, which runs in a while( condition ){ run function } loop. I would like to know if there is a way to get the outputs in different windows, every time the function runs, so as to compare easier the results. 2) In my

Hi there, This problem has been dogging me for a bit, and I'm trying to figure out why. When running the the subsets function in the leaps library, R is giving me the following error message > lvodsub <- subsets(pred, resp$LVOD) Warning message: XHAUST returned error code -999 in: leaps.exhaustive(a, really.big = really.big) but this still happens if I add the really.big option: